Dana Fisman

Senior Academic

SyGuS-comp 2017

Results and analysis

Rajeev Alur, Dana Fisman, Rishabh Singh, Armando Solar-Lezama

Syntax-Guided Synthesis (SyGuS) is the computational problem of finding an implementation f that meets both a semantic constraint given by a logical formula j in a background theory T, and a syntactic constraint given by a grammar G, which specifies the allowed set of candidate implementations. Such a synthesis problem can be formally defined in SyGuS-IF, a language that is built on top of SMT-LIB. The Syntax-Guided Synthesis Competition (SyGuS-Comp) is an effort to facilitate, bring together and accelerate research and development of efficient solvers for SyGuS by providing a platform for evaluating different synthesis techniques on a comprehensive set of benchmarks. In this year's competition six new solvers competed on over 1500 benchmarks. This paper presents and analyses the results of SyGuS-Comp'17.

Publication language English
Pages 97-115
Journal Electronic Proceedings in Theoretical Computer Science, EPTCS
Volume 260
Publication status Published - 28.11.2017

ASJC Scopus subject areas

Software
Access to Document
10.4204/EPTCS.260.9
Other files and links
Link to publication in Scopus